The sampling technique of simple random sampling is a sampling method that provides equal opportunities for each member of the population to be selected as a sample. This sampling technique randomly selects the sample from the existing population. To be able to use the simple random sampling technique, researchers need to ensure that there are at least two assumptions that must be met.

The two assumptions are that there is a sample frame and homogeneous population members. If these two assumptions have been met, the researcher can choose a simple random sampling technique to select a number of samples from the observed population.

The researcher should not use simple random sampling if these two assumptions are not met. Researchers can use several alternative sampling techniques according to the characteristics of the population being observed.

In the sampling technique using simple random sampling, researchers need to understand well how to take random samples. There are several ways that researchers can use to select samples from the population being studied randomly.

Examples of sampling techniques that can be used are random tables or other techniques that ensure that each member of the population has the same opportunity to be selected as the sample.

The sampling technique using simple random sampling can quickly be done using Excel. On this occasion, Kanda Data will write a tutorial on how to randomly select samples from the observed population using the simple random sampling technique.

**Example of Sampling Technique Using Simple Random Sampling**

The sampling technique using simple random sampling is done by giving each member of the observed population an equal opportunity to be selected as a sample. An example of a case study a researcher will observe vegetarian consumers in a community.

It is known that the researcher has collected data on a population of 20 vegetarian consumers. In this study, the researcher will take a random sample of 50% of the total observed population of vegetarian consumers. Detailed data on population names and names of vegetarian consumers can be seen in the table below:

Based on the table above, the researcher will take a sample of 50%, so the number of samples taken is 10 vegetarian consumers. What is the technique for selecting a sample of 10 vegetarian consumers from the total population observed?

Here, Kanda Data only give an example of a population of 20 vegetarian consumers. It is intended to make understanding the random sample selection technique easier. In fact, the observed population generally has a large sample size.

**How to Select a Random Sample Using Excel**

There are several ways that researchers can use to select a random sample. One way that can be used is to use the sampling menu on the data analysis toolpak in Excel.

The previous article was written with the title: “** How to Activate and Load the Data Analysis Toolpak in Excel**“. This article discusses a tutorial on how to enable the Data Analysis menu in Excel.

The steps for randomly selecting samples in Excel are opening Excel where the serial number and name of the respondent have been entered. Then click the Data menu, and select the Data Analysis menu in the upper right corner.

After clicking Data Analysis, a Data Analysis window will appear, containing options for several analysis tools. The next step is that the researcher needs to look for sampling on the available analysis tools. Then select sampling and click ok.

After the researcher clicks ok, the Sampling window will appear. Researchers can input serial number data of population members of 20 vegetarian consumers, including their labels. Next, the researcher needs to click enable label.

In the sampling method, choose random and fill in the number of samples as much as 10. It follows the research objective of taking a random sample of 50% of the total population observed.

Therefore, the number of samples is filled with 10 vegetarian consumers. Furthermore, output options can be saved on the same Excel sheet. In detail, the sampling steps using Excel can be seen in the image below:

After clicking Ok, an output containing the 10 serial numbers of the selected sample data will appear. The serial number of the sample data has been randomly selected using Excel from 20 populations of vegetarian consumers. The output sampling using simple random sampling in Excel can be seen in detail in the image below:

Based on the picture above, it can be seen that the selected sample numbers of the 20 vegetarian consumer populations are serial numbers 19; 3; 12; 7; 6; 15; 18; 4; 14; and 19. It shows that the sample has been taken randomly from the population using Excel.

This technique can be applied to large populations; even populations above 5,000 can easily be randomly sampled. It is the tutorial that I can write at this time. Hopefully useful for all of you. Wait for educational article updates the following week. Thank you.

[…] Simple random sampling is a technique where each element in the population has an equal chance of being selected as a sample, assuming that the population is homogeneous and a sample frame is available. Stratified random sampling, on the other hand, is a method where the population is divided into homogeneous subgroups or strata, and random samples are drawn from each stratum. […]